JacksonBlellockA7Code.py

import numpy as np

import pandas as pd

import dash

from dash import Dash, dcc, html, Input, Output

import plotly.express as px

dataDictionary = {

'Year': [1930, 1934, 1938, 1950, 1954, 1958, 1962, 1966, 1970, 1974, 1978, 1982, 1986, 1990, 1994, 1998, 2002, 2006, 2010, 2014, 2018, 2022],

'Winner': ['Uruguay', 'Italy', 'Italy', 'Uruguay', 'Germany', 'Brazil', 'Brazil', 'England', 'Brazil', 'Germany', 'Argentina', 'Italy', 'Argentina', 'Germany', 'Brazil', 'France', 'Brazil', 'Italy', 'Spain', 'Germany', 'France', 'Argentina'],

'RunnerUp': ['Argentina', 'Czechoslovakia', 'Hungary', 'Brazil', 'Hungary', 'Sweden', 'Czechoslovakia', 'Germany','Italy', 'Netherlands', 'Netherlands', 'Germany', 'Germany', 'Argentina', 'Italy', 'Brazil','Germany', 'France', 'Netherlands', 'Argentina', 'Croatia', 'France']

soccerData = pd.DataFrame(dataDictionary)

championCounts = soccerData['Winner'].value_counts().reset_index()

championCounts.columns = ['Country', 'Wins']

isoMap = {

'Brazil': 'BRA',

'Germany': 'GER',

'Italy': 'ITA',

'Argentina': 'ARG',

'Uruguay': 'URY',

'England': 'ENG',

'France': 'FRA',

'Spain': 'ESP'

championCounts['isoAlpha'] = championCounts['Country'].apply(lambda c: isoMap.get(c, None))

app = Dash(__name__)

app.layout = html.Div([

html.H1("FIFA World Cup Finals", style={'textAlign': 'center'}),

dcc.Tabs([

dcc.Tab(label="All Winners", children=[

html.Br(),

html.H2("Countries That Have Won the World Cup"),

dcc.Markdown(

"*This tab displays all countries that have won the World Cup.*"

),

html.Div(id="allWinnersDiv", style={'marginTop': '15px'})

]),

dcc.Tab(label="Countrys Amount of Wins", children=[

html.Br(),

html.H2("Choose a Country to See Its World Cup Wins"),

dcc.Dropdown(

id="countryDropdown",

options=[{'label': c, 'value': c} for c in championCounts['Country'].unique()],

placeholder="Select a country..."

),

html.Div(id="countryWinsOutput", style={'marginTop': '15px', 'fontWeight': 'bold'})

]),

dcc.Tab(label="Final by Year", children=[

html.Br(),

html.H2("Select a World Cup Year for Winner & Runner-Up "),

dcc.Dropdown(

id="yearDropdown",

options=[{'label': y, 'value': y} for y in soccerData['Year'].unique()],

placeholder="Pick a year..."

),

html.Div(id="yearWinnerRunnerupOutput", style={'marginTop': '15px', 'fontWeight': 'bold'})

]),

dcc.Tab(label="Map of World Cup Winners", children=[

html.Br(),

html.H2("World Cup Wins by Country"),

dcc.Graph(id="winsChoroplethFig")

])

])

@app.callback(

Output("allWinnersDiv", "children"),

Input("countryDropdown", "value")

def showAllWinners(_ignore):

allWinnersList = championCounts['Country'].unique()

return html.Ul([html.Li(country) for country in allWinnersList])

@app.callback(

Output("countryWinsOutput", "children"),

Input("countryDropdown", "value")

def showCountryWins(chosenCountry):

row = championCounts[championCounts['Country'] == chosenCountry] if chosenCountry else pd.DataFrame()

return "" if row.empty else f"{chosenCountry} has won the World Cup {row['Wins'].values[0]} time(s)."

@app.callback(

Output("yearWinnerRunnerupOutput", "children"),

Input("yearDropdown", "value")

def showYearlyWinnerRunnerup(chosenYear):

row = soccerData[soccerData['Year'] == chosenYear] if chosenYear else pd.DataFrame()

return "" if row.empty else f"In {chosenYear}, the winner was {row['Winner'].values[0]} and the runner-up was {row['RunnerUp'].values[0]}."

@app.callback(

Output("winsChoroplethFig", "figure"),

Input("countryDropdown", "value")

def updateMap(_ignoreCountry):

fig = px.choropleth(

championCounts,

locations="isoAlpha",

color="Wins",

hover_name="Country",

title="Total World Cup Wins by Country",

color_continuous_scale=px.colors.sequential.Plasma,

range_color=(0, championCounts['Wins'].max()),

labels={'Wins': 'Number of Wins'}

)

fig.update_layout(margin={"r":0, "t":50, "l":0, "b":0})

return fig

if __name__ == '__main__':

app.run(debug=True)